josephbakarji / deep-delay-autoencoderLinks
Discovers high dimensional models from 1D data using deep delay autoencoders
☆38Updated 2 years ago
Alternatives and similar repositories for deep-delay-autoencoder
Users that are interested in deep-delay-autoencoder are comparing it to the libraries listed below
Sorting:
- ☆379Updated 4 years ago
- Code and files related to random side projects☆21Updated 4 years ago
- ☆200Updated 10 months ago
- mathLab mirror of Python Dynamic Mode Decomposition☆113Updated 11 months ago
- SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification of Nonlinear Dynamics☆161Updated 4 years ago
- Deep learning assisted dynamic mode decomposition☆19Updated 4 years ago
- neural networks to learn Koopman eigenfunctions☆467Updated last year
- A package for computing data-driven approximations to the Koopman operator.☆406Updated 3 weeks ago
- ☆69Updated last year
- PySHRED: Package for Shallow Recurrent Decoding☆28Updated 7 months ago
- Code for paper Sparse identification of nonlinear dynamics with Shallow Recurrent Decoder Networks.☆35Updated this week
- SINDy (Sparse Identification of Nonlinear Dynamics) algorithms☆79Updated 3 years ago
- Symbolic Identification of Non-linear Dynamics. The method generalizes the SINDy algorithm by combining sparse and genetic-programming-ba…☆85Updated 3 years ago
- Codes for Linear and Nonlinear Disambiguation Optimization (LANDO)☆32Updated 4 years ago
- A data-driven method to calculate the Lyapunov exponent of a dynamical system employing a GRU-RNN.☆47Updated last year
- ☆274Updated 3 years ago
- ETH Zürich Deep Learning in Scientific Computing Master's course 2023☆122Updated last year
- Consistent Koopman Autoencoders☆75Updated 2 years ago
- PDE-VAE: Variational Autoencoder for Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning☆36Updated 4 years ago
- ☆241Updated 4 years ago
- ☆199Updated last year
- An interpretable data-driven framework for building generative reduced order models with embedded uncertainty quantification☆47Updated 3 weeks ago
- ☆12Updated 3 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆83Updated 3 years ago
- Transformers for modeling physical systems☆148Updated 2 years ago
- ☆50Updated 2 years ago
- This repository contains a number of Jupyter Notebooks illustrating different approaches to solve partial differential equations by means…☆181Updated 4 years ago
- Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…☆61Updated 3 years ago
- Implementing a physics-informed DeepONet from scratch☆56Updated 2 years ago
- A simulation of the Kuramoto-Sivashinsky Equation in Python and MATLAB☆28Updated 7 years ago